Fault Type Detection in Distribution System Based on

Proceedings National Graduate Conference 2012 (NatGrad2012), Universiti Tenaga Nasional, Putrajaya Campus, 8-10 Nov 2012

Fault Type Detection in Distribution System Based on Clarke Transform and Phase-Shift Angle of Voltage Waveforms Eyada A Alanzi , Mahmoud A Younis ELECTRICAL POWER ENGINEERING COLLEGE OF ENGINEERING UNIVERSITI TENAGA NASIONAL 43009 KAJANG, SELANGOR, MALAYSIA [email protected]

ABSTRACT Distribution power systems are exposed to various unexpected failure due to many random causes. These failures have a negative impact on the reliability and availability of the system. Accurate detection of these faults will help in restoration of power in a timely manner and not to cause any severe damage to the power system equipment. This paper investigates the problem of accurate detection of fault types occurred in the distribution system. The proposed technique uses features extracted from the voltage waveforms recorded from one end of the distribution system during fault occurrence. Clarke’s Transformation criterion is used to identify if the fault is from line-toground (grounded fault) or from phase-to-phase (ungrounded fault). Fault types are then classified by the high performance comparison method of voltage waveform using phase-shift angles before and after the fault occurrence. Different types of faults (single-lineto-ground, double-line-to-ground, phase-phase and balanced three-phase) that are occurred at different locations, fault resistances and inception angles are tested and analyzed. Results from simulation of faults on a model of 33 KV distribution system typical networks are presented. Validation of fault type detection is performed using ATP/EMTP transient simulations and MATLAB software applications. Keywords: Distribution System, Fault Type Detection, Modal Transformation, Phase-Shift Angle. 1. Introduction Overhead distribution systems, among all other electrical components of the network, are exposed to different types of unexpected failures due to various random causes. These failures have a negative impact on the availability and reliability of the system. Accurate classification and detection of these faults will assist in restoration of power in a timely manner and not to cause any severe damage to the power system equipment. There are several methods, in the last three decades, used for classification and detection of faults on the overhead distribution systems. Many

researchers used Wavelet transform to classify the fault type signal. Maximum detail coefficient, signal energy and ratio of energy change of three phase current signals are detection tools of wavelet transform [1-2]. Voltage and current waveforms are used by wavelet transform to classify faults in a double line network for only single-phase-ground faults [3]. Also, Spectral energy tested at certain thresholds by wavelet transform. The current magnitude, phase angle difference and spectral energy of coefficients are analysed for detection of fault types. The threshold value is to be modified in each case with new actual data [4]. [Other researchers used Clarke Transform with Neural network to classify the fault type [5].] In this method Neural Network results depends on training of input data that may takes time to converge. This paper investigates the problem of accurate classification of fault types occurred in distribution system. The proposed algorithm uses the features of voltage waveform recorded from one end of the distribution system during fault occurrence. Fault type detection consists of two parts. In the first part, distinctive features of faulty voltage signals are extracted by using Clark Transformation to verify between grounded and ungrounded faults. In the second part, Voltage phase-shift angles of pre- and post fault occurrence period are calculations to differentiate between faulty and un-faulty phases. Different types of faults (single-line-to-ground, double-line-to-ground, phase-phase and balanced three-phase) that are occurred at different locations are analyzed. Results from simulation of faults on a model of 33KV distribution power system are presented. Validation of classification of fault type is performed using ATP/EMTP transient simulations and MATLAB software applications. 2. Classification and Fault Location Techniques Modal Transformation (MT) and voltage phase-shift angle (PSA) criteria are tools used in the fault type detection in distribution systems technique. These tools performance is dependent on the features of voltage waveforms recorded during the event of fault.

Proceedings National Graduate Conference 2012 (NatGrad2012), Universiti Tenaga Nasional, Putrajaya Campus, 8-10 Nov 2012

2.1 Modal Transformation (MT) In the proposed approach, to determine whether the fault is grounded or ungrounded, the modal components are extracted from the phase domain signals by the modal transformation matrix. In this study, all overhead distribution line models are assumed to be fully transposed, and therefore the well known Clarke’s constant and real transformation matrix will be used for this purpose. The matrix is given by [6] and stated as follows: 2/√6 = � 0 1/√3

−1/√6 1/√2 1/√3

−1/√6 −1/√2� 1/√3

2/√6 𝑉𝛼 �𝑉𝛽 � = � 0 𝑉0 1/√3

−1/√6 1/√2 1/√3

−1/√6 𝑉𝑎 −1/√2� * �𝑉𝑏 � 𝑉𝑐 1/√3

T

(1)

The phase signals are transformed into their modal components by using this transformation matrix as in (2).

ungrounded. In the grounded fault situation, faulted phases of single-line-to-ground, double-line-to-ground and Three-line-to-ground will be distinguished. Similarly, for ungrounded fault situation, line-to-line fault and three lines fault will be determined. 2.2 Phase-Shift Angle (PSA) criterion Phase shift is a change in voltage phase angle associated with fault occurrence. The characteristics of particular faults at certain locations are determined by the type of fault in addition to other factors [7]. Phase shift during the fault occurrence can be obtained by calculating the difference between the pre-fault voltage waveform angle and the during-fault voltage waveform angle. A phase shift can be expressed either as a time (in milliseconds), or as an angle (in degrees or radians), and may have a negative or positive values.

3. Distribution System Model

where,

𝑉𝛼 Smode = �𝑉𝛽 � 𝑉0

(2)

𝑉𝑎 and Sphase = �𝑉𝑏 � 𝑉𝑐

The Smode and Sphase are the modal and phase signals (voltages or currents) vectors respectively. Clarke’s transformation is real and can be used with any transposed line. If the studied line is not transposed, then an eigenvector based transformation matrix, which is frequency dependent, will have to be used. This matrix should be computed at a frequency equal or close to the frequency of the initial fault transients. Recorded three phase signals are first transformed into their modal components. Clarke’s transformation matrix can be used to obtain the aerial and ground mode signals from the three-phase transients. The first two modes (mode α and mode β), are usually referred to as the areal modes, and the third (mode 0) is referred to ground mode and its magnitude is significant only during faults having a path to ground. The fault phase type problem is formulated based essentially on the ground (mode 0) making use of the ground mode magnitude for the purpose of distinguishing between grounded and ungrounded faults situations. Therefore, equation (2) can be rewritten as 𝑉𝑎 V0 = �1/√3 1/√3 1/√3� * �𝑉𝑏 � (3) 𝑉𝑐

Based on the V0 value in (3), the fault situation can be decided either the fault scheme is grounded or

Determination and classification of faults is performed on a power system model simulated in Fig. 1. The simulation of transient signals of the overhead distribution system is performed using ATP/EMTP program [8]. The power system is consisting of single power supply of 33kv, 50Hz and a radial over head distribution system of 30 km with tapped loads. The faults are simulated on different points on the power system. Faulted phases are simulated with different fault resistances (Rf) (1Ω, 10Ω most studies indicated that the Rf value will not exceed more than 10Ω) and impact of different inception angles (Ai) (0° and 45°) of faults are studied. Fault phase types (single-line-toground, double-line-to-ground, three-line-to-ground, phase-phase and balanced three-phase) with different fault resistances and inception angles are simulated and analysed. The simulation time is 60 ms with time step 1.0μs and total of 1200 samples for each fault case. A 10 KM

T1

Load

Fig.1: study

10 KM

T2

T3 10 KM

Load

Load

Overhead Distribution System used for the

System parameters are typical to Kuwait network at Wafra area with generator source resistance 0.89Ω and source inductance of 12.37mH. Overhead distribution line parameters for main line and lateral branches are shown in Table 1.

Proceedings National Graduate Conference 2012 (NatGrad2012), Universiti Tenaga Nasional, Putrajaya Campus, 8-10 Nov 2012

(AG) fault at 10km from sending end with fault resistance of 1Ω and at load.

Table 1 Overhead Distribution line parameters 0.11763 Ω/km 0.22961 Ω/km 0.3712 Ω/km 1.0717 Ω/km 3.1 µF/km 1.5 µF/km

R1 R0 X1 X0 C1 C0

4. Fault Classification Algorithm

Sampling of three-phase of voltage waveforms is shown in Fig. 2 & Fig.3 during the occurrence of single-line-to-ground (phase-A-to-ground) and double-line-to-ground (phases-AB-to-ground) faults, respectively.

The classification algorithm of faulted phase type is divided into two parts as shown in Fig. 5. One part is to determine if the fault is grounded or ungrounded by using the Clarke Modal and Wavelet Transformations. The second part is to determine the faulted phase by the calculation of voltage waveform phase-shift angle value for each phase. [The values of the three phases indicate which phase is in fault.] In Fig. 5, the phase shift values are given the weight of large (L) or small (S) for comparison between the resulted phase-shift angles of each phase to indicate the fault type.

Read Va, Vb, Vc x 10

4

4

3

Vc

Voltage, V

2

1

Apply Clarke Modal Transform

Normalize

Va

0

Vb -1

Calculate Phase-Shift Angle (PSA) for Va, Vb, Vc

-2

-3

-4 10

0

20

30

40

50

60

Time, ms

Fig. 2: Using ATP/EMTP the Measured Voltage at main substation (point A) during single-line-to-ground (AG) fault at 10km from sending end with fault resistance of 1Ω and at no-load.

Y PSAa = PSAb = PSAc = 0 No Fault

N

Fault Exist

Y

V0 < 0.1

N

Fault Type

4

x 10

4

3

Vc

2 Voltage, KV 1

Vb

0

-1

Va

-2

Voltage Phase Shift value due to Fault L = Large , S = Small

V0 ≥ 0.1 GROUNDED

V0 < 0.1

PSa

PSb

PSc

UNGROUNDED

AG

L

S

S

Y

N

BG

S

L

S

Y

N

CG

S

S

L

Y

N

ABG

L

L

S

Y

N

BCG

S

L

L

Y

N

ACG

L

S

L

Y

N

AB

L

L

S

N

Y

BC

S

L

L

N

AC

L

S

L

N

Y

ABCG

L

L

L

NA

NA

Y

-3

-4

0

10

20

30 Time, ms

40

50

60

Fig. 3: Using ATP/EMTP the Measured Voltage at main substation (point A) during line-to-line (AB) fault at 10km from sending end at no-load.

Fig.5: Flow chart of developed Fault Type Classification.

4

x 10

3

5. Results and Discussions 2 Vb 1 Voltage, KV

Va

0

-1 Vc -2

-3

0

10

20

30 Time, ms

40

50

60

Fig. 4: Using ATP/EMTP the Measured voltage at main substation (point A) during single-line-to-ground

Equation (3) is applied to the simulated faulted voltage waveforms recorded at the main substation (point A) during single line to ground fault and line to line fault. The resulted signals are shown in Fig. 6 and Fig. 7. Our concern here is the value of V0 which indicate the grounded and ungrounded fault by its value. Note that in Fig. 6 (grounded case) the value is very high compared to the value of Fig.7 (ungrounded case).

Proceedings National Graduate Conference 2012 (NatGrad2012), Universiti Tenaga Nasional, Putrajaya Campus, 8-10 Nov 2012

4

manner. Last column designate if calculated values are matching with proposed method conditions and lead to the same fault type (YES or NO).

x

4 3 2

V0

Magnitud 1 0

Table 2 Phase-shift angle and V0 values for voltage waveforms during faults at 10km away from sending end with no-load condition.

-

2

2

3 Time,

3

4

Fig.6: Using EMTP the Modal transform of voltage waveforms during single line-to-ground fault at 10Km from sending end with fault resistance 10 Ω.

Fault Type AG BG CG

4

x

4

ABG

3

BCG

2 1

ACG

V0

0

AB

-

BC

-

AC 2

2

3 Time,

3

4

Fig. 7: Using EMTP the Modal transform of voltage waveforms during line-to-line fault at 10Km from sending end Which shows value 0 due to ungrounded fault. In the next step, the phase-shift angle value is calculated. Table.2 shows the values of phase-shift angles. From these values, it is clear to predict the faulted phase in each fault type case. As per condition above, when the PSA value is close or equal to zero then the phase is not faulty. V0 is able to detect the grounded or ungrounded cases except for three phase faults where it is not applicable. Instead, the phase values of three phase faults are close to each other and none is close to zero, hence there is no need for V0 to make comparison. Results data in Table.2 and Table.3 are clear evidence on the accuracy of proposed classification method. MATLAB software is used for calculation of data in modal transformation and phaseshift angle [9].

ABCG

A validation data set consisting of different fault types was generated using the power system model shown in Fig. 1. For different fault types and fault location the effects of these factors on the performance of the proposed algorithm is investigated. Results with different system conditions is presented in Table 2 and Table 3. As an example, test results for a single phase to ground, BG fault at 10 km from the main substation is presented in the second row of the Table 4. For this fault, V0=1.09 which indicate ground fault (> 0.1) and PSAa=0.000482568 (S), PSAb=0.115919721(L) and PSAc=0.000338411(S) which satisfies the condition of fault at phase B to ground as indicated in proposed method flow chart in Fig.5. All values of V0 and PSAs in Table 2 and Table 3 can be verified in the same

PSb

PSc

0.048950 155 0.000482 568 0.000545 897 0.034633 139 0.000319 154 0.060185 154 0.249324 469 0.000000 001 0.351957 156 0.039076 127

0.000065 246 0.115919 721 0.000170 070 0.067074 773 0.092004 953 0.000121 707 0.565607 648 0.101564 311 0.000000 007 0.101901 714

0.000070 248 0.000338 411 0.085941 561 0.000209 358 0.116463 858 0.070271 800 0.000000 016 0.471001 883 0.122222 600 0.085527 525

V0 > 0.1 (Y) or (N) 0.33513511 4 (Y) 1.09022058 3 (Y) 1.42724897 2 (Y) 66.1797305 21 (Y) 64.4931837 22 (Y) 1.29898641 7 (Y) 0.00071408 2 (N) 0.00159686 2 (N) 0.00025492 4 (N) NA

Matching YES or NO YES YES YES YES YES YES YES YES YES YES

Table 3 Phase-shift angle and V0 values for voltage waveforms during faults at 30km away from sending end with load condition. Fault Type AG BG CG ABG BCG ACG AB BC AC

5.1 Results Validation

PSa

ABCG

PSAa

PSAb

PSAc

0.1412541 57 0.0070889 60 0.0083689 14 0.1243793 90 0.0012349 82 0.1755149 11 0.1283842 24 0.0000000 00 0.3324277 83 0.1591545 31

0.0078516 30 0.1019563 84 0.0103723 25 0.1310767 31 0.0843668 43 0.0020967 79 0.2642558 85 0.0763809 47 0.0000000 00 0.1079594 47

0.0086684 95 0.0059248 49 0.1496410 14 0.0022987 25 0.1162661 69 0.1289525 01 0.0000000 00 0.2344840 97 0.1580232 27 0.1553030 06

V0 > 0.1 (Y) or (N) 6.898456 756 (Y) 3.688935 246 (Y) 3.205316 383 (Y) 2.601579 643 (Y) 5.449664 660 (Y) 2.853698 420 (Y) 0.000716 616(N) 0.001086 208(N) 0.002693 542 (N) NA

Matching YES or NO YES YES YES YES YES YES YES YES YES YES

6. Conclusion A new fault type detection algorithm for distribution power system is presented in this paper. Application of Modal Transformation (MT) and Phase-Shift Angle (PSA) criterion have greatly demonstrate accurately the proposed algorithm. The algorithm has been studied with different fault resistances of (1Ω, 10Ω) and different inception angles of (0° and 45°) and showed an accurate results.

Proceedings National Graduate Conference 2012 (NatGrad2012), Universiti Tenaga Nasional, Putrajaya Campus, 8-10 Nov 2012

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